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Logo Ngram Statistics Package 1.09

by tpederse - August 12, 2008, 18:21:52 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5849 views, 1268 downloads, 0 comments, 1 subscription

About: The Ngram Statistics Package is a suite of Perl modules that identifies significant multi-word units (collocations) in written text using many different tests of association. NSP allows a user to [...]

Changes:

Initial Announcement on mloss.org.


Logo Torch 3

by bengio - November 13, 2007, 01:38:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5835 views, 1559 downloads, 1 subscription

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About: Torch is a statistical machine learning library written in C++ at IDIAP,

Changes:

Initial Announcement on mloss.org.


Logo BMRM 2.1

by chteo - May 8, 2009, 08:08:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5801 views, 1126 downloads, 1 subscription

About: BMRM is an open source, modular and scalable convex solver for many machine learning problems cast in the form of regularized risk minimization problem.

Changes:

Initial Announcement on mloss.org.


Logo JMLR EnsembleSVM 2.0

by claesenm - March 31, 2014, 08:06:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5793 views, 2052 downloads, 2 subscriptions

About: The EnsembleSVM library offers functionality to perform ensemble learning using Support Vector Machine (SVM) base models. In particular, we offer routines for binary ensemble models using SVM base classifiers. Experimental results have shown the predictive performance to be comparable with standard SVM models but with drastically reduced training time. Ensemble learning with SVM models is particularly useful for semi-supervised tasks.

Changes:

The library has been updated and features a variety of new functionality as well as more efficient implementations of original features. The following key improvements have been made:

  1. Support for multithreading in training and prediction with ensemble models. Since both of these are embarassingly parallel, this has induced a significant speedup (3-fold on quad-core).
  2. Extensive programming framework for aggregation of base model predictions which allows highly efficient prototyping of new aggregation approaches. Additionally we provide several predefined strategies, including (weighted) majority voting, logistic regression and nonlinear SVMs of your choice -- be sure to check out the esvm-edit tool! The provided framework also allows you to efficiently program your own, novel aggregation schemes.
  3. Full code transition to C++11, the latest C++ standard, which enabled various performance improvements. The new release requires moderately recent compilers, such as gcc 4.7.2+ or clang 3.2+.
  4. Generic implementations of convenient facilities have been added, such as thread pools, deserialization factories and more.

The API and ABI have undergone significant changes, many of which are due to the transition to C++11.


Logo mSplicer 0.3

by sonne - May 18, 2008, 13:07:40 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5761 views, 1200 downloads, 3 subscriptions

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About: For modern biology, precise genome annotations are of prime importance as they allow the accurate definition of genic regions. We employ state of the art machine learning methods to assay and [...]

Changes:

Initial Announcement on mloss.org.


Logo Sleipnir 1.0

by chuttenh - June 30, 2008, 03:22:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5755 views, 1280 downloads, 1 subscription

About: The Sleipnir C++ library implements a variety of machine learning and data manipulation algorithms focusing on heterogeneous data integration and efficiency for large biological data collections.

Changes:

Initial Announcement on mloss.org.


Logo GibbsLDA 0.2

by pxhieu - May 9, 2008, 22:18:52 CET [ Project Homepage BibTeX Download ] 5749 views, 2548 downloads, 1 subscription

About: GibbsLDA++: A C/C++ Implementation of Latent Dirichlet Allocation (LDA) using Gibbs Sampling for parameter estimation and inference. GibbsLDA++ is fast and is designed to analyze hidden/latent topic [...]

Changes:

Initial Announcement on mloss.org.


Logo hca 0.61

by wbuntine - September 10, 2014, 03:33:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5718 views, 1107 downloads, 4 subscriptions

About: Multi-core non-parametric and bursty topic models (HDP-LDA, DCMLDA, and other variants of LDA) implemented in C using efficient Gibbs sampling, with hyperparameter sampling and other flexible controls.

Changes:

Corrections to diagnostics and topic report. Correction to estimating alpha. Now estimating beta sometimes (when estimating phi).


Logo Python Robotics 5.0.0

by dsblank - January 22, 2008, 20:25:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5704 views, 1170 downloads, 1 subscription

About: The goal of the project is to provide a programming environment for easily exploring advanced topics in artificial intelligence and robotics without having to worry about the low-level details of [...]

Changes:

Initial Announcement on mloss.org.


Logo LSTM for biological sequence analysis 1.0

by mhex - July 28, 2010, 16:32:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5699 views, 1348 downloads, 1 subscription

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About: Implementation of LSTM for biological sequence analysis (classification, regression, motif discovery, remote homology detection). Additionally a LSTM as logistic regression with spectrum kernel is included.

Changes:

Spectrum LSTM package included


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